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Tytuł artykułu

Comparison of Acoustocerebrography Measurement and Magnetic Resonance Imaging Methods in the Assessment of White Matter Lesions in Patients with Atrial Fibrillation

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The brain is subject to damage, due to ageing, physiological processes and/or disease. Some of the damage is acute in nature, such as strokes; some is more subtle, like white matter lesions. White matter lesions or hyperintensities (WMH) can be one of the first signs of micro brain damage. We implemented the Acoustocerebrography (ACG) as an easy to use method designed to capture differing states of human brain tissue and the respective changes. Aim: The purpose of the study is to compare the efficacy of ACG and Magnetic Resonance Imaging (MRI) to detect WMH in patients with clinically silent atrial fibrillation (AF). Methods and results: The study included 97 patients (age 66.26 ± 6.54 years) with AF. CHA2DS2-VASc score (2.5 ±1.3) and HAS BLED (1.65 ± 0.9). According to MRI data, the patients were assigned into four groups depending on the number of lesions: L0 – 0 to 4 lesions, L5 – 5 to 9 lesions, L10 – 10 to 29 lesions, and L30 – 30 or more lesions. Authors found that the ACG method clearly differentiates the groups L0 (with 0-4 lesions) and L30 (with more than 30 lesions) of WMH patients. Fisher’s Exact Test shows that this correlation is highly significant (p < 0.001). Conclusion: ACG is a new, easy and cost-effective method for detecting WMH in patients with atrial fibrillation. The ACG measurement methodology should become increasingly useful for the assessment of WMH.
Rocznik
Strony
445--452
Opis fizyczny
Bibliogr. 32 poz., tab., wykr.
Twórcy
  • District Hospital, Cardiology, Radom, Poland
  • Fraunhofer Institute for Cell Therapy and Immunology IZI, Leipzig, Germany
  • Department of Radiology, Military Institute of Medicine, Warsaw, Poland
  • Department of Radiology, Military Institute of Medicine, Warsaw, Poland
  • Medical University of Warsaw, Warsaw, Poland
  • Department of Ultrasound, Institute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland
  • Department of Gerontology, Public Health and Didactics, National Institute of Geriatrics, Rheumatology and Rehabilitation, Warsaw, Poland
Bibliografia
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  • 3. Chugh S. S. et al. (2014), Worldwide epidemiology of atrial fibrillation – A Global Burden of Disease 2010 Study, Circulation, 129 (8): 837-847, doi: 10.1161/circulationaha.113.005119.
  • 4. De Cocker L. J. et al. (2018), Clinical vascular imaging in the brain at 7T, NeuroImage, 168: 452-458, doi: 10.1016/j.neuroimage.2016.11.044.
  • 5. Debette S., Markus H. S. (2010), The clinical importance of white matter hyperintensities on brain magnetic resonance imaging: systematic review and metaanalysis, BMJ, 341: c3666, doi: 10.1136/bmj.c3666.
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  • 7. Dobkowska-Chudon W. et al. (2018), Detecting cerebrovascular changes in the brain caused by hypertension in atrial fibrillation group using acoustocerebrography, PLoS ONE, 13 (7): e0199999, doi: 10.1371/journal.pone.0199999.
  • 8. Freedman B., Potpara T. S., Lip G. Y. (2016), Stroke prevention in atrial fibrillation, Lancet, 388 (10046): 806-817, doi: 10.1016/S0140-6736(16)31257-0.
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  • 17. Maillard P. et al. (2012), Effects of systolic blood pressure on white-matter integrity in young adults in the Framingham Heart Study: a cross-sectional study, Lancet Neurology, 11 (12): 1039-1047, doi: 10.1016/S1474-4422(12)70241-7.
  • 18. Maniega S. M. et al. (2016), Integrity of normal-appearing white matter: influence of age, visible lesion burden and hypertension in patients with small-vessel disease, Journal of Cerebral Blood Flow & Metabolism, 37 (2): 644-656, doi: 10.1177/0271678X16635657.
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  • 29. White W. B. et al. (2018), Relationships among clinic, home, and ambulatory blood pressures with small vessel disease of the brain and unctional status in older people with hypertension, American Heart Journal, 205: 21-30, doi: 10.1016/j.ahj.2018.08.002.
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  • 31. Wrobel M., Dabrowski A., Kolany A., Olak-Popko A., Olszewski R., Karlowicz P. (2015), On ultrasound classification of stroke risk factors from randomly chosen respondents using non-invasive multispectral ultrasonic brain measurements and adaptive profiles, Biocybernetics and Biomedical Engineering, 36 (1): 18-28, doi: 10.1016/j.bbe.2015.10.004.
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Uwagi
Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e81f7729-f763-4066-bfd8-5ff4f3fafa49
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